Attention-based deep learning in forensic anthropology: Validation of YOLOv12 architecture for automated skeletal fracture detection
- DOI
- 10.1016/j.forsciint.2026.113175
- Published
- 2027-01
- Container
- Forensic Science International
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.forsciint.2026.113175,
title = {Attention-based deep learning in forensic anthropology: Validation of YOLOv12 architecture for automated skeletal fracture detection},
author = {Cumali Çatak and Mert Ocak},
year = {2027},
journal = {Forensic Science International},
doi = {10.1016/j.forsciint.2026.113175},
url = {https://doi.org/10.1016/j.forsciint.2026.113175}
}RIS
TY - JOUR TI - Attention-based deep learning in forensic anthropology: Validation of YOLOv12 architecture for automated skeletal fracture detection AU - Cumali Çatak AU - Mert Ocak PY - 2027 JO - Forensic Science International DO - 10.1016/j.forsciint.2026.113175 UR - https://doi.org/10.1016/j.forsciint.2026.113175 ER -
APA
Çatak, C., & Ocak, M. (2027). Attention-based deep learning in forensic anthropology: Validation of YOLOv12 architecture for automated skeletal fracture detection. Forensic Science International. https://doi.org/10.1016/j.forsciint.2026.113175
Source records
- crossref · retrieved 2026-11-09T22:03:01.715Z